Hello
I am Suparna
I am a fifth-year Ph.D. student at National University of Singapore, advised by Prof. Vaibhav Rajan . I am interested in addressing problems in Healthcare using Deep Learning, specifically in using multiple data sources and their interpretability. I have also worked on wearable data to personalize interventions for increasing physical activity.
During my Masters at IIITB, I learned Machine Learning, and Deep Learning (with Automatic Speech Recognition) as part of coursework and attempted application to Images, Speech, Biomedical Images, and Fitness Data.
Current Affiliation
PhD (Information Systems and Analytics), National University of Singapore (NUS)
[Aug 2019 - current]
Clinical Data Analytics Lab, DISA, NUS
Education
M.Tech. (IT with Data Science specialization) - International Institute of Information Technology, Bangalore (IIIT-B)
B.E. (Computer Engineering) - Savitribai Phule Pune University [I2IT, Pune]
Publications
Evaluating Explanations from AI Algorithms for Clinical Decision-Making: A Social Science-based Approach, Suparna Ghanvatkar and Vaibhav Rajan, accepted at IEEE Journal of Biomedical and Health Informatics (J-BHI), DOI: 10.1109/JBHI.2024.3393719
Theory-driven Evaluation of Usefulness of Explanations in Clinical Decision Support Systems, Suparna Ghanvatkar and Vaibhav Rajan, Conference on Health IT and Analytics CHITA 2023
Towards a Theory-Based Evaluation of Explainable Predictions in Healthcare, Suparna Ghanvatkar, Vaibhav Rajan, Short Paper, International Conference on Information Systems ICIS 2022, Copenhagen, Denmark. PDF
Temporal Personalization of a Digital Intervention for Physical Activity, Suparna Ghanvatkar, Saurabh Chaudhari, Atreyi Kankanhalli, Short Paper, Pacific Asia Conference on Information Systems PACIS 2022. PDF
Personalization of Intervention Timing for Physical Activity: Scoping Review, Saurabh Chaudhari, Suparna Ghanvatkar, Atreyi Kankanhalli, JMIR Mhealth Uhealth 2022;10(2):e31327, DOI: 10.2196/31327
Deep Recurrent Neural Networks for Mortality Prediction in Intensive Care using Clinical Time Series at Multiple Resolutions, Suparna Ghanvatkar, Vaibhav Rajan, Short Paper, International Conference on Information Systems ICIS 2019, Munich, Germany. PDF
User Models for Personalized Physical Activity Interventions: A Scoping Review , Suparna Ghanvatkar, Atreyi Kankanhalli, Vaibhav Rajan, JMIR mHealth and uHealth, JMIR Mhealth Uhealth 2019;7(1):e11098. DOI: 10.2196/11098
Detecting Temporal Pattern Profiles from Smartphones for User Activity Analysis, Suparna Ghanvatkar, Vaibhav Rajan, Atreyi Kankanahalli, Short Paper, International Conference on Information Systems ICIS 2018, San Francisco, USA. PDF
Research Experience
NUS Singapore - Mortality prediction in Intensive Care (Jun 2018 - Jun 2019)
NUS Singapore - Personalization for physical activity based on fitness data (Jan -May 2018)
Mazumdar Shaw Medical Foundation - Necrosis Identification for Glioblastoma H&E slides (Aug-Nov 2017)
VideoKen - Automatic Speech Recognition for Indian accented English (May-July 2017)